Chemical detection system and method using a capacitive trans impedance amplifier

ABSTRACT

The exemplary embodiments provide a method, system, and device for identifying chemical species in a sample. According to one embodiment, the method, system, and device may include introducing a sample gas into a differential ion mobility device, ionizing at least a portion of the sample gas to generate at least one ion species, filtering the at least one ion species between a pair of filter electrodes, generating a detection signal in response to the at least one ion species depositing a charge on a collector electrode, and detecting a spectral peak associated with the at least one ion species.

RELATED APPLICATIONS

This application also claims the benefit of U.S. Provisional ApplicationNo. 61/021,575, filed Jan. 16, 2008, which is incorporated by referenceherein in its entirety. This application is a continuation-in-part ofU.S. application Ser. No. 11/748,258, filed on May 14, 2007, entitled“Method and System for Detecting Vapors,” which is incorporated byreference herein in its entirety.

FIELD OF THE INVENTION

The exemplary embodiments relate generally to a system, method anddevice to identify compounds in a sample gas based on ion mobilitycharacteristics. More particularly, the present embodiments relate to adevice to identify compounds using differential ion mobilityspectrometry.

BACKGROUND OF THE INVENTION

Current events underscore the need for an improved and inexpensiveanalytical device capable of rapidly, reliably, and accurately detectingexplosives, toxic chemicals and biologics, chemical warfare agents, andother harmful materials. Spectrometers based on ion mobility have beenpreviously developed to serve this purpose, but technologicalimprovements are still needed to reduce detection time, increasesensitivity, enable environment adaptability, reduce noise interference,improve prediction accuracy, and reduce power consumption.

Conventional spectrometers typically employ either ion-mobilityspectrometry (IMS) or differential ion mobility spectrometry (DMS) asthe broad method by which they identify compounds in a sample gas takenfrom an ambient environment. Conventional IMS devices, which are wellknown in the art, are based on time-of-flight (TOF-IMS) analysis.TOF-IMS identifies compounds by measuring the time it takes ions totravel through a drift tube, usually on the order of milliseconds, froma shutter-gate to a detector electrode. The drift time is dependent onthe mobility of ions in a linear, low electric field, which acceleratesthe ions in the drift tube. The measured drift time is characteristic ofthe ion species present in the sample. In IMS systems, an ion's mobilitycoefficient is independent of the electric field strength but itsvelocity is proportional to the electric field strength.

Though typical IMS and DMS based devices share many of the same systemcomponents (inlet system, ionization source, readout electronics) DMSdevices operate very differently. DMS devices characterize chemicalsubstances using differences in the gas phase mobilities of ions inalternating, high-frequency, asymmetric electric fields. Ions areseparated as they are carried by drift gas between two-parallel platesor filter electrodes. At higher electric field strengths there is anonlinear dependence of ion mobility. A high-frequency asymmetricelectric field is produced by applying a high-frequency asymmetricdifferential potential between the plates. An equivalent field could beproduced by applying a differential potential to both plates relative toground, or to one of the plates with the other grounded. This appliedfield, referred to as the separation or dispersion voltage, causes ionsto oscillate perpendicular to the gas flow. Some ions traverse thefilter electrodes, while others gradually move towards one of theelectrodes and eventually collide with an electrode, which neutralizethe electric charge in such ions. Only ions with a net velocity ordifferential mobility of zero transverse to the applied electric fieldwill pass through the electrodes.

The net migration of the ions can be corrected with a compensationvoltage (Cv), which is a weak dc voltage superimposed on thehigh-frequency, asymmetric electric field, to correct the path ionstravel so they do not move towards an electrode.

Various techniques of DMS have been developed, including field ionspectrometry (FIS), transverse field compensation ion mobilityspectrometry, ion non-linearity drift spectrometer, field asymmetric ionmobility spectrometry (FAIMS), and radio frequency ion mobilityspectrometry (RFIMS), among others.

However, current devices that use DMS to identify compounds, althoughimproved over conventional TOF-IMS systems, still have deficiencies thatmust be improved, like reductions in detection time, noise, and powerconsumption; increases in sensitivity; and improvements in environmentadaptability, and prediction accuracy.

SUMMARY OF THE INVENTION

In a first exemplary embodiment, a method is provided for identifyingchemical species in a sample. The method includes introducing a samplegas into a differential ion mobility device, ionizing at least a portionof the sample gas to generate at least one ion species, filtering the atleast one ion species between a pair of filter electrodes, generating adetection signal using a capacitance trans impedance amplifier (CTIA) inresponse to the at least one ion species depositing a charge on acollector electrode, the CTIA sending the detection signal to a signalprocessor, and detecting a spectral peak associated with the at leastone ion species by processing the detection signal and referencing adata store to identify an unknown compound in the species.

In another exemplary embodiment, a device is provided for identifyingchemical species in a sample gas. The device includes an inlet adaptedto receive a sample gas, the inlet being selectively separated from anionization region that ionizes the sample gas to generate ions, a filterhaving at least a pair of oppositely disposed filter electrodes definingan analytical gap between which a substantially asymmetric field isgenerated, the substantially asymmetric field being controllable by asignal generator, wherein the filter separates the ions based on ionmobility characteristics, at least one collector electrode adapted toreceive the ions, the collector being coupled to an capacitive transimpedance amplifier (CTIA), and a signal processor adapted to receive anoutput voltage generated by the CTIA in order to detect a spectral peakassociated with the ions.

BRIEF DESCRIPTION OF THE FIGURES

Advantages of the exemplary embodiments will be apparent to those ofordinary skill in the art from the following detailed descriptiontogether with the appended drawings, in which like reference numeralsare used to indicate like elements:

FIG. 1 illustrates a block diagram of an exemplary device for detectingchemical species based on analytes in a carrier gas.

FIG. 2 illustrates a more detailed block diagram of an alternativeexemplary device for detecting chemical species based on analytes in acarrier gas.

FIG. 3 illustrates a block diagram of an exemplary moisture controlsystem for use in an exemplary device for detecting chemical speciesbased on analytes in a carrier gas.

FIG. 4 illustrates an exemplary embodiment of the analytical regionwithin the device.

FIG. 5 illustrates a chart showing the field-dependent mobility of threedifferent ion species under various electric fields using an exemplaryvapor detector.

FIGS. 6A and 6B illustrate an exemplary embodiment of a capacitive transimpedance amplifier, and an exemplary timing diagram associatedtherewith, used in the device.

FIGS. 7A and 7B illustrate exemplary spectra of sample gas at dryconditions and wet conditions based on analyte analysis performed by anexemplary device.

FIG. 8A illustrates reactant ion peak locations for a sample gas atvarious moisture levels.

FIG. 8B illustrates a mathematical trend for reactant ion peak locationsfor a sample gas at various moisture levels.

FIG. 9 illustrates exemplary spectra of sample gas generated based onanalyte analysis performed by an exemplary device.

FIG. 10 illustrates an exemplary block diagram for detecting chemicalspecies based on analytes in a carrier gas using an exemplary device.

FIG. 11 illustrates an exemplary block diagram of an algorithm processto identify an ion species based using a known reactant ion peak.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description provides a description and understanding ofexemplary embodiments for a system, method, and device to identifycompounds, in a sample gas, based on ion mobility characteristics. Thesystem and method, however, are not limited to these exemplaryembodiments. Moreover, one of ordinary skill in the art, after readingthe following description, will appreciate the use of the exemplaryembodiments for their intended purpose and benefit in a number ofalternative embodiments.

The exemplary embodiments described herein have particular applicationto high-frequency ion-mobility spectrometry. The exemplary embodimentsprovide for an improved system and method to identify and discriminatebetween compounds that exist in a sample gas analyzed using differentialmobility spectrometry. Generally, the exemplary embodiments describe asystem and method that collects a sample gas, ionizes that sample gasinto ions (also referred to as analytes), carries those ions typicallywith a carrier gas through a filtering section that applies analternating, asymmetric electric field to the ions, and detects oridentifies compounds based on ion mobility characteristics. The appliedelectric field has a varying influence on the unknown ions travelingbetween the filter electrodes, and the behavior of the ions, in responseto the applied electric field, allows for different species of ions tobe identified by comparing detected ion peak locations to known datastored within a processor in the device.

FIG. 1 illustrates a block diagram that shows an exemplary embodiment ofa device 100 that may be used to analyze a sample gas, and directly orindirectly identify one or more compounds contained therein. A samplegas may be introduced into the device 100 from an ambient airenvironment. In an exemplary embodiment, the device 100 may be adifferential mobility spectrometer (DMS) detector, a field asymmetricion mobility spectrometry (FAIMS) detector, a field ion spectrometry(FIS) detector, a radio frequency ion mobility spectrometry (RFIMS), orany other type of detector capable of analyzing a gas and identifyingcompounds based on ion mobility characteristics.

In operation, sample gas may be introduced into the inlet region 110 ofthe device 100 from an ambient air environment. The sample gas flowsinto an ionization region 120. There, one or more compounds in thesample may be ionized by an ionization source to generate ions oranalytes of chemical species present in the sample gas. The ions may becarried by a carrier gas from the ionization region 120 to theanalytical region 130, which typically consists of two, oppositelydisposed filter electrodes (not shown) that define an analytical gap. Inthe analytical gap, an alternating, asymmetric field may be appliedbetween the filter electrodes to filter the ions based on differences inion mobility, which may be influenced by ion size, shape, mass, andcharge. Ions that pass through the analytical region 130 then flow tothe detection region 140, which may consist of a pair of oppositelycharged collector electrodes (not shown), one positive and one negative.A detection signal may be generated using a capacitive trans impedanceamplifier (CTIA), as ions deposit their charges on the collectorelectrodes. Stated differently, the CTIA amplifies the signal from thecollector electrodes and provides an amplified signal representing thedetected ion current to a signal processor 150. The signal may then beprocessed using the signal processor 150 to identify compounds in thesample gas. The signal processor may communicate those identificationsto a readout display 160 where they may be displayed. In an exemplaryembodiment, the readout display 160 may be an LCD or other displaytechnology that displays a visual alert with information regarding theidentifications. In another exemplary embodiment, the readout display160 may be a speaker that emits an audible sound for identifyingpurposes. Though the device 100 may be described as having regions, suchregions are for description purposes only, are not limited to actualphysical locations within the device 100, and may overlap or becombined. Each region within the device 100 will be further described indetail below.

The device 100 may be adapted to detect various species within gassampled from an ambient air environment. The species that device 100 maybe capable of identifying may include, but are not limited to, chemicalwarfare agents, nerve agents, blister agents, choking agents, toxicindustrial chemicals (TICs), toxic industrial materials (TIMs), lowvapor compounds, explosives, narcotics, biologics, pathogens, organicchemicals, inorganic chemicals, hydrocarbons, or combinations thereof.

As recited above, the device 100 may comprise a series of regions thatare fluidly connected in order for the device 100 to identify one ormore compounds in a sample gas. Those regions may include the inletregion 110, the ionization region 120, the analytical region 130, thedetection region 140, the signal processor 150, and the readout display160. Each subsystem may have features contained within that will befurther described below.

The inlet region 110 may be the sample collection subassemblyresponsible for drawing a sample from the environment into the device100. In an exemplary embodiment, the inlet region 110 may serve twofunctions: sample collection and introduction. The inlet region 110 mayalso concentrate the sample, filter the sample, or provide a selectivebarrier between the analytical region 130 and the environment.

FIG. 2 illustrates a block diagram of an exemplary device for detectingchemical species based on analytes in a carrier gas. The inlet region110 may have a inlet opening 202 adapted to receive a sample gas asinput to the device 100 from the ambient environment. The inlet region110 may comprise a heated element or other heating device, such as aheated vacuum transfer line (not shown) followed by a membrane 206. Asampling pump 204 may be coupled to an outlet (not shown), through whichexcess sample gas may be discharged. The pump 204 may create a vacuumfor drawing the sample gas from an ambient air environment into theinlet 202. A heating element or other heating device may facilitate theflow of the sample gas through the inlet region 110, and may preventchemical species within the sample gas from adhering to a wall in thedevice 100, for example. The vacuum side of the pump 204 may be attachedto the heated transfer line to pull a sample from the environmentthrough the heated transfer line and across the membrane 206. Not all ofthe sample, however, may permeate through the membrane 206, and anyexcess sample gas will be exhausted back into the environment, bypassingother subsystems in the device 100.

The membrane 206 may be gas-permeable and may reside inside of the inletregion 110, separating the inlet region 110 from the ionization region120. The membrane 206 may permit some or all of the molecules orcompounds in the sample gas to diffuse across the membrane 206 and flowinto the ionization region 120. The membrane 206 may selectively blockcertain molecules from passing though to the ionization region 120. Themembrane 206 may be one of two types of membrane: a thin film membraneor an oil membrane. A thin film membrane may comprise a solid materialstretched to a known thickness with a known permeability. An oilmembrane may be a thin, porous substrate coated or conditioned, or both,with oil. Integrating a membrane of either type into the inlet region110 may permit for a more efficient transfer of the sample gas throughthe device 100. The membrane 206 may be designed such that it eliminatesreduced permeation rates for chemical species of interest, which, if noteliminated, may cause a decrease in sensitivity. The membrane 206 may bedesigned to reduce the chance that species chemically bind to themembrane 206, which may degrade the membrane 206. The membrane 206 maybe configured to withstand a range of temperatures and environments thatthe device 100 may be exposed to and used in. The membrane 206 mayfurther prevent contaminants from being introduced into the ionizationregion 120.

The membrane 206 may prevent moisture from passing through the inletregion 110 to the ionization region 120. As will be discussed below, ithas been discovered that moisture significantly impacts the spectra ofidentified ions, and therefore, it may be desirable to maintain themoisture level within a known range. The membrane 206 may be configuredsuch that it helps maintain a moisture level within the device 100 ofbetween about 100 parts per million (ppm) and about 1000 ppm, forexample. However, the range of moisture level in the device 100 may bechanged as necessary or desired. The membrane 206 may be made of anysuitable material, thickness, or surface area, to improve its permeationcharacteristics to allow molecules of interest to pass efficiently fromthe inlet region 110 to the ionization region 120. The temperature maybe controlled across the membrane 206, and it may be held at varioustemperatures, either uniform or gradient. The type, geometry, andlocation of the membrane 206 used in the inlet system 110 may contributeto a quicker and more reliable detection process and result. A specificmembrane or sample control mechanism may be selected for particulardetection applications. The membrane temperature may be optimized/setbased on the characteristics of the analyte of interest. As analytes maybe optimized at different temperatures to one another, it is sometimespossible to optimize the membrane conditions for a range of analytes bycreating a temperature gradient across the membrane by holding the outersupported part of the membrane at one temperature and allowing thecenter region to stabilize at another temperature.

Still referring to FIG. 2, the inlet region 110 may be optimized in avariety of ways in order for the device 100 to operate efficiently,consistently, and reliably. For example, problems that may be avoided byan optimizing the inlet region 110 include substantially reducingpockets of the sample gas in the interior of the inlet region 110. Thesepockets may cause an initial decrease in the sample gas available forpermeation across the membrane 206, which may later lead to falsesignals due to extended clear down times as the pocket of sample gasslowly diffuses from the inlet walls through the membrane 206 to theionization region 120 over time. Other ways to optimize the inlet region110, may include selecting a durable and reliable membrane material forthe given or expected sample environment, establishing a temperaturegradient through the inlet region 110, and maintaining a substantiallyconstant rate at which the sample may be pumped through the inlet region110.

FIG. 3 is a block diagram of an exemplary embodiment of a moisturecontrol system 300 used in the device 100. The device 100 may be adaptedto control the moisture or moisture content of the gas passing throughthe device 100. For example, the device 100 may require that themoisture content of the carrier gas, which carries the ions and flowsthrough the analytical region 120, to be within a particular range,e.g., 100 ppm to 1000 ppm.

In an exemplary embodiment, the moisture control system 300 may includea moisture sensor 310 connected to a moisture sensor controller 312. Themoisture sensor 310 may be suitably disposed in the gas flow. Forexample, the moisture sensor 310 may be disposed in the analyticalregion 130 of the device 100. The moisture sensor 310 senses at leastone parameter of the gas and outputs a signal representing the at leastone parameter to a moisture sensor controller 312. The moisture sensorcontroller 312 analyzes the at least one parameter the moisture contentof the gas. Any known sensor may be used to collect data suitable forascertaining the moisture content in the gas. The moisture content ormoisture level may be adjusted based on the moisture sensed by themoisture sensor 312.

In another embodiment, the moisture sensor 310 may not be a physicalcomponent or sensor that is incorporated into the device. Instead,monitoring the water/vapor content of the gas may be accomplished by thedevice 100 itself. For example, a reactant ion peak (RIP), which isexplained in further detail below, is sensitive to changes in themoisture content of the gas—i.e., the positive and negative RIP of a DMSinstrument using water chemistry is very sensitive to changes inmoisture content. Therefore, the properties of the device—the positiveion peak location (V_(c))—may be used as the moisture control for thegas. In other words, the moisture can be controlled by monitoring theposition of the RIP position.

The moisture control system 300 may include a gas flow line 360. Gas maypass through an outlet 320 into the gas flow line 360. As shown in FIG.3, the gas may circulate through the gas flow line 360 in a closed loopmanner. In other words, the gas may pass out of the outlet 320 into thegas flow line 360, then pass through various components disposed alongthe gas flow line 360, and back into the inlet region 110 in the device100. In one embodiment, the gas flows into the inlet region 100 acrossthe back side of the membrane 206 (referring to FIG. 2). During suchcirculation, the moisture in the gas may be controlled. A pump 340 maybe used to pump the gas through the gas flow line 360.

The moisture control system 300 may include at least one scrubber 330.In an exemplary embodiment, the moisture control system 300 may have twoscrubbers 330 disposed along the gas flow line 360, as shown in FIG. 3.The one or more scrubbers 330 may be provided to remove contaminatesfrom the circulating gas. The scrubber 130 may be disposed in the gasflow line 360 as desired. For example, a scrubber 330 may be disposedimmediately after the gas exits the outlet 320 or a scrubber 330 may bedisposed immediately before the gas enters the inlet region 110.

As disclosed herein, a “scrubber” may be described as any medium orsubstance capable of removing contaminates from the gas. The scrubbermay be used to remove such contaminates, and not to remove moisture fromthe gas. Accordingly, the scrubber 330 may comprise any medium, such asactivated charcoal, capable of removing analytes and other contaminatingmaterials from the gas. In an exemplary embodiment, the scrubber 330 maybe provided to remove analytes or contaminating vapors from the carriergas (used to transport ions through an analytical region of adifferential mobility spectrometer) in a spectrometer. It is expectedthat any such scrubber material will have some capacity to absorbmoisture. However, in the applications of the moisture control system300, it may be advantageous to use a scrubber material with a relativelylow saturation point for moisture absorption. This characteristic may beuseful in being able to condition the scrubber 330 to a specific levelof moisture, capable of maintaining the carrier gas or other gas towithin a range of moisture content, required for the optimal performanceof the device 100.

The moisture control system 300 may also includes a dryer 350. Asdisclosed herein, a “dryer” may be described as any medium or substancecapable of removing moisture from the gas. The dryer 350 may be used toremove moisture, and not to remove contaminates from the gas. In anexemplary embodiment, the dryer may include a drying agent. The dryeragent may be any material or desiccant capable of removing moisture fromthe gas, e.g. air or carrier gas used in the device 100. A molecularsieve, as is well known in the art, may be a very efficient dryer andmay be capable of binding water molecules to itself and not releasing itback to the carrier gas until it reaches a high saturation point. Amolecular sieve may be well suited to function in the moisture controlsystem 100 to take out excess moisture from the carrier gas, and thusmaintain a desired moisture level for the gas. It is recognized that amolecular sieve, or other dryer that is utilized, may also remove somecontaminants.

As shown in FIG. 3, the gas flow line may include a primary pass-throughline 362 and a secondary pass-through line 364. The secondarypass-through line 364 may include the dryer 350, whereas the primarypass-through line 362 may not. The carrier gas circulating through maybe controlled to flow through either the primary pass-through line 362or the secondary pass-through line 364.

A pair of dryer valves 342 may be provided to control which pass-throughline the gas passes. In an exemplary embodiment, the moisture controlsystem 300 may have a pair of valves 342. The first valve 342 mayselectively control the gas flow to pass into the primary pass-throughline 362 or the secondary pass-through line 364. The second valve 364may selectively control the gas flow to exit from the primarypass-through line 362 or the secondary pass-through line 364. In anexemplary embodiment, the dryer valves 342 may be controlled by themoisture sensor controller 312. As described above, the moisture sensor310, disposed in the gas flow, senses at least one parameter of the gasand outputs this information to the moisture sensor controller 312. Theat least one parameter may provide the data to the moisture sensorcontroller 312 by which the moisture sensor controller 312 may determinethe moisture content of the gas. Based on the determination of themoisture in the gas, the moisture sensor controller 312 switches thevalves 342 so that the gas flows through either the primary pass-throughline 362 or the secondary pass-through line 364. The moisture sensorcontroller 312 may maintain the moisture between an upper and a lowerthreshold value as desired. It is appreciated that the particularmoisture range will depend on the needs of the particular conditions.

Referring back to FIGS. 1 and 2, in an exemplary embodiment, sample gasmay enter may flow across the membrane 206, where sample moleculespermeate from one side of the membrane 206 to the other side. A carriergas, which may be separated from the sample gas, may then sweep acrossthe back side of the membrane 206 and carry the sample molecules intothe ionization region 120. The molecules of the sample gas passingthrough the membrane 206 to the ionization region 120 may be referred toas analytes. In the ionization region 120, the sample gas, carrying oneor more analytes to be detected, may be subjected to an ionizationsource. In an exemplary embodiment, the device 100 may have more thanone ionization source. The one or more ionization sources may ionize theanalytes, which react in an ion reaction region, such as throughatmospheric pressure chemical ionization. The one or more ionizationsource may be a Nickel 63 (Ni63) source, a corona, a plasma source, a UVlamp, or other known sources for ionizing chemicals. Also, the one ormore ionization source may be plasma generators for ionizing theanalytes. Other radioactive materials, such as, for example, Americiumalso may be used for as an ionization source for ionizing the analytes.The type of ionizing source may be selected based on the preferred ionaffinity of the analytes, and power and life required from the ionizingsource. After the analytes are ionized, they may pass through the ionreaction region and into the analyzer section 130.

FIG. 4 illustrates an exemplary analytical region 130 of an exemplarydevice for detecting chemical species based on analytes in a carriergas. Referring to FIGS. 2 and 4, the analytical region 130 may bedownstream of the ionization region 120 and upstream of the detectionregion 140. A purpose of the analytical region 130 may be to selectivelyseparate the ion species before they collide with one or more collectorelectrodes 220 (shown in FIG. 2) in the detection region 140. Toseparate the ion species before they collide with the one or morecollector electrodes (not shown), a field strength (E), generated by anasymmetric waveform generator 420, and a small DC voltage (Ec), areapplied to one of two parallel filter electrodes 410. Ions pass betweenthe filter electrodes 410, also referred to as parallel electrodeplates. An alternating, asymmetric electric field, the exemplary shapeof which is shown at the top of FIG. 4, may be developed between thefilter electrodes 410 and be transverse to the gas flow. FIG. 2 alsoshows an exemplary embodiment of the asymmetric field 250 developedbetween the filter electrodes. The ions oscillate and move in a zigzagmotion between the filter electrodes 410, as the field switches frompositive to negative, toward the detection region 140. The net “drift”of an ion towards one electrode 410 or another at a field strength maybe dependent on a characteristic difference between the ion's mobilityat high and low fields. Ions that do not have a balance between highfield and low field mobility will drift into one of the filterelectrodes 410 and be neutralized.

The asymmetric waveform effectively separates ions based on their fieldmobility dependence. If only the variable field strength is used, theanalytical gap can only “detect” ions already in equilibrium (no netdrift) because all other ions will collide with the filter electrodes410, thereby losing their charge. In other words, as charged ions passthrough the analytical region 130, some are neutralized as they collidewith the filter electrodes 410, while others pass to the detectionregion without losing their charge 140. For some ions to pass throughthe analytical region 130, an additional DC voltage may be appliedacross the filter electrodes 410 to create an additional electric field.This DC voltage may be called the compensation voltage (Ec). Thecompensation voltage shifts the paths of the rest of the ions throughthe analytical region 130 so that “unbalanced” ions may selectivelybecome balanced and will pass through to the detection region 140.

In the analytical region 130, the concentration of ions of one speciesreaching the collector electrode 220 can be calculated as the followingboundary value problem that is solved from t=0 to t=l/v, integrating nat the collector electrode 220 (distance l from the ionization source)over a width of −de/2 to de/2 (the effective gap):

$\begin{matrix}{\frac{\partial n}{\partial t} = {\overset{->}{\nabla}\left( {{n\overset{->}{V}} - {D{\overset{->}{\nabla}n}}} \right)}} & \lbrack 1\rbrack \\{\overset{->}{V} = {{K(E)}\overset{->}{E}}} & \lbrack 2\rbrack \\{E = {{E(t)} + E_{c}}} & \lbrack 3\rbrack \\{d_{e} = {d - \delta}} & \lbrack 4\rbrack \\{\delta = {\frac{1}{2}{\int_{0}^{t_{1} + t_{2}}{{\overset{->}{V}}\ {\mathbb{d}t}}}}} & \lbrack 5\rbrack\end{matrix}$where:

-   -   de=the “effective gap” between the parallel plates    -   d=the width of the gap between the parallel plates    -   δ=the magnitude of the oscillations between the plates in one        period of the asymmetric waveform.    -   l=the length of the parallel plates    -   v=the velocity of the carrier gas through the analytical region    -   n=is the concentrations of ions (1 species)    -   t=time    -   t₁=the time under high frequency conditions (see FIG. 4)    -   t₂=the time under low frequency conditions (see FIG. 4)    -   V=the velocity of the ions    -   D=diffusion coefficient    -   K(E)=the field mobility dependence under the electric field E    -   E=the electric field between the parallel plates    -   E(t)=electric field of asymmetric waveform at time t    -   E_(c)=compensation voltage        (Note that Equation 3 must be modified for cylindrical plate        geometry because the electric field is nonuniform. Also note        that Equation 5 is only valid for an asymmetric waveform that is        a step function. A different waveform will require a change to        Equation 5.)

The field strength E(t) is a function of time because it alternatesbetween high and low frequency fields. The mobility of ions changes withthe strength of the field, and the net difference between low and highfield mobility is the characteristic that is used to separate differention species. For example, FIG. 5 depicts the mobility of three differention species at different field strengths. Notice that mobility generallyincreases as the field strength increases. For some ions, however, suchas Species A, as shown in FIG. 5, mobility may begin to decrease past acertain field strength. The maximum field strength that can be achievedbefore arcing occurs is dependent on the width between the filterelectrodes 410, and the pressure within the analytical region 130.Larger gaps and higher pressures allow stronger field strengths to beused.

The compensation voltage (E_(c) in Equation 3) is the small amount of DCvoltage applied across one filter electrode 410 to bring different ionspecies into “equilibrium” such that those species reach the detectionregion 140.

The width of the analytical region 130, i.e., the distance between thefilter electrodes 410, (d in Equation 4) has an effect on both the peakwidths and sensitivity that are produced by the detection region 140. Asmaller gap between the two filter electrodes 410 may cause more ions tobe annihilated as they hit the electrodes 410. This can decreasesensitivity because some of the ions in “equilibrium” may touch thesides due to diffusion or oscillation between positive and negativefields. It can also create narrower peaks in the DMS spectra. If the gapbecomes smaller than the width of the oscillations (δ in Equation 4) ofan ion between positive and negative fields, then the ion will not bedetected. This is because the ion may collide with a filter electrode410 before reaching the detection region 140 (even when in equilibrium).A very large gap may increase sensitivity, but may create wider peaksand may be more likely to allow two similar species, with slightlydifferent mobilities, to pass through to the sensor (a decrease inselectivity).

The length, l, of the analytical region 130 determines the duration oftime in Equation 1. Longer analytical regions will cause losses insensitivity due to increased chances for ions colliding with the filterelectrodes 410. However, specificity may be increased because as thelength increases, “equilibrium” must be met more precisely to pass allthe way to the detection region 140.

The velocity of the carrier gas v determines the duration of time inEquation 1. If the gas flow is too fast and ions reach the detectorplate before they have time to separate, there will be poor separation.If the gas flow is too slow, diffusion will continually cause the ionsin equilibrium to diffuse to the parallel plates and be annihilated.Peak widths may also be wider in some instances when the flow of thecarrier gas is too slow.

The frequency of the asymmetric waveform that determines the intensityof the electric field over time is contained within the function E(t).If the frequency is too low, then the distance traveled by the ions asthey oscillate increases. As this distance becomes greater there is anincreased chance of colliding with the parallel plates and decreasingsensitivity. This also can create narrower peaks in the spectra due to adecrease in the “effective gap,” d_(e). Higher frequencies have bettersensitivity, but they may produce wider peaks in the DMS spectra.

The mobility at a field strength E is K(E). As discussed previously (seefield strength E(t)), the mobility of an ion may be a function of theelectric field, Mobility can also change as other environmentalconditions change, such as moisture, pressure, and temperature. Themobilities under a single set of environmental conditions must be knownfor the current field strength (field strength parameter above).

The concentration of ions entering the analytical region 130 is n att=0. The intensity value is a single number that is the sum of thepositive and negative charged ions that hit the detector electrodeswithin the range of the “effective gap” de (oscillations will preventions from reaching the detector at the edges of the gap) over time.

The geometry of the analytical region 130 can be either flat plate orcylindrical. FIG. 4 depicts a flat plate design. A cylindrical designhas cylindrical plates rather than flat parallel plates. Flat platedesigns may have a uniform electric field throughout the analyticalregion, and the cylindrical plate design, has a nonuniform electricfield. Equation 1 is able to simulate flat plate geometry because theuniform electric field is dependent only on time (t). However, for acylindrical design the electric field will be a function of both time,for the asymmetric waveform, and location, for the non-uniform electricfield. Cylindrical designs allow the use of a “resolution voltage” thatallows peaks to be sharpened by adding an additional electric field (notused in Equation 1).

The diffusion coefficient (D in Equation 1) of an ion is a physicalproperty of each ion that must be experimentally determined. Diffusionwill also increase as temperature and pressure increase. Diffusioncauses a loss of sensitivity and can cause wider peaks in the DMSspectra. Diffusion has a cumulative effect, so longer analytical regions(l) and slower drift velocities (v) will increase the effect ofdiffusion.

An increase in pressure increases ion mobility due to an increasednumber of collisions between ions. Increases in pressure also increasediffusion, which causes a loss of sensitivity if not for a largerincrease in sensitivity due to a larger number of ions passing throughthe analytical region 130 (same concentration of ions at higherpressure=many more ions). The increase in diffusion (D in Equation 1)causes an increase in peak widths in the DMS spectra.

Complex ion chemistry occurs within the drift region as ions arerepeatedly attracted together into clusters and broken apart as theymove through the analytical region 130. If multiple compounds arepresent, new ion species may be created in the middle of the analyticalregion 130 that will quickly be annihilated because they will no longerbe in equilibrium. Charge competition between different ion species mayoften prevent one of the species from creating more ions than the other.

An increase in temperature will cause a moderate increase in ionmobility. It also increases the rate of diffusion (less sensitivity andpossibly wider peaks).

Ion mobility is also significantly influenced by moisture due to aninduced dipole moment of an ion species that is caused by nearby watermolecules. This increase in mobility is reflected in Equation 1 withinK(E).

The shape of the asymmetric waveform is determined by the function E(t)in Equation 1. Different asymmetric waveforms can be made by changingthe function E(t).

The parameters explained above are inputs in the analytical region 130and are outputted as an intensity value, which is the integral of theion concentrations that reach the detection region 140 over a specifiedamount of time. Several of these parameters are not simply numbers to beoptimized, but are physical properties of ions or the collectorelectrodes 210. For example, the mobility of an ion at different fieldstrengths is a physical property of ion species, and the diffusion rateis another physical property of each species (dependent on pressure andtemperature).

The wave form generator 420, also shown in FIG. 4, may be controlled bya signal generator (not shown). Known signal generators may be used toachieve this purpose. The signal generator may generate an electricfield between the filter electrodes 410 that is transverse to thecarrier gas flow in the analytical gap—the space between the filterelectrodes 410. As previously recited, the electric field between thefilter electrodes 410 filters ion analytes based on variouscharacteristics of the ions. The electric field may be an asymmetricradio frequency (RF) field, which also may be referred to as a filterfield, a dispersion field, or a separation field. Field strength of theelectric field may vary based on the applied asymmetric RF voltage(sometimes referred to as dispersion or separation voltage) and on theradial distance between the electrodes 410.

The signal generator uses various AC and DC voltages and frequencies tofilter the ionized analytes within the carrier gas passing between thefilter electrodes 410 in the analytical region 130. The signal generatormay generate the electric field that biases ionized analytes of interestalong a central path between the electrodes 410. As explained above, thealternative, asymmetric electric field transversely displaces ionsbetween the electrodes 410, with each chemical species being displaced adistance toward the electrodes 410 per cycle of the electric field. Dueto ions having different size and mass, the electric field may cause theions not of interest to be attracted to either of the electrodes 410,which then neutralizes the ions not of interest from the carrier gas.

To form the electric field, the signal generator may generate anelectrical waveform that passes through an amplifier (described below)and onto the filter electrodes 410. The signal generator may be batteryoperated or externally powered, for example. The electrical waveform maybe an asymmetric radio frequency (RF) alternating current (AC) voltage,for example. The electrical waveform also may include a direct current(DC) voltage, which may be referred to as a compensation voltage. Thecompensation voltage reduces the alternating attraction to the filterelectrode caused by the asymmetric RF AC voltage to maintain ionizedanalytes of interest on a central path between the filter electrodes410. The amount of compensation voltage depends upon characteristics ofthe chemical species, and may be used to identify the presence orabsence of a particular chemical species in the sample gas. Thecompensation voltage is applied to the electrodes 410 with theasymmetric RF voltage to compensate for the displacement of ions from aparticular chemical species offsetting transverse displacement generatedby the alternating asymmetric RF voltage. The compensation voltagereduces or substantially eliminates net transverse displacement of theionized analytes of that chemical species, which enables those ionizedanalytes to pass between the filter electrodes 410. The ions that do notpass between the filter electrodes 410 undergo a net displacement andare neutralized on contact with either filter electrode 410.

Referring back to FIG. 2, after passing between the filter electrodes410 and through the analytical region 130, carrier gas may transport theremaining filtered ionized analytes along a flow path to the detectionregion 150. The detection region 150 may comprise one or more collectorelectrodes 220 that are each electrically coupled to an amplifier 230.In an exemplary embodiment, there may be a positive detection mode and anegative detection mode in the detection region 140. The positivedetection mode refers to positive ions passing through the filterelectrodes 410 that are then detected by a negatively biased collectorelectrode 220. The negative detection mode refers to negative ions,passing through the filter electrodes 410, that are then attracted toand detected by a positively biased collector electrode 220. Having twocollector electrodes 220, one positive and the other negative, enablessimultaneous detection of positive and negative ion species, as positiveand negative ions are generated in the ionization region 120 and areintroduced into the analyzer region 130. It should be noted that certainchemical species may form both positive and negative ions in theionization region 120. Data from both the positive and negative modesmay be used in a single detection to identify the compounds in thesample.

When the positive and negative ions collide with one or the othercollector electrodes 220, a charge may be deposited on the collectorelectrode 220. That charge may be amplified by respective amplifiers 230to provide detection data for use in the signal processor 160 foridentification of the detected ion species. The amplifiers 230 maymeasure the electrical current caused by the ionized analytes collidingwith the collector electrodes 220 at a particular compensation voltage.The electrical current may be used to identify the presence or absenceof a chemical species based on a comparison and matching with theelectrical current response of known chemical species.

Each collector electrode may be connected to a dedicated amplifier. FIG.6 shows an exemplary embodiment of the amplifier 230. In an exemplaryembodiment, one or more amplifier 230 may be capacitive trans impedanceamplifiers (CTIAs). Amplifiers of this type are particularly sensitivefor reading out small charge quantities. Each CTIA amplifier 230typically includes an operational amplifier having a negative inputconnected to an element and a positive input connected to an arrayoffset bias voltage, which permits either positive or negative ions tobe processed. The output of the amplifiers 230 may be fed back to thenegative input through a feedback capacitor, having a value. Typicalvalues for the capacitor of the CTIA amplifier 230 may be 3 picofarads(pF), 12 pF, 25 pF, or 50 pF. The output of the amplifiers 230 may becoupled to the input to the signal processor 150. The amplifier 230takes a very small current input from the collector electrodes 220 andconverts it into a voltage. In an exemplary embodiment, each amplifier230 may have one or more feedback capacitors, C₁-Cn, and a normally openreset switch that is in parallel with the one or more feedbackcapacitors. The reset switch, when closed, may discharge the one or morecapacitors. The output from each amplifier 230 may be sent to the signalprocessor 150. Typical values for the current deposited on the collectorelectrodes 220 may range from 10 pico amperes (pA) to 100 pA. Typicalvalues for the voltage outputted by the amplifier 230 may be 0 volts (V)to 3 V. The voltage may be calculated using the transfer function shownin FIG. 6, Vout=1/C*₀∫^(t) l_(in)*dt. The voltage may be directed to thesignal processor 150. There, the voltage may be converted in the signalprocessor 150 into a digital value using an analog-to-digital converter(ADC) module so that the digital magnitude can be processed by a digitalprocessing module, such as a microprocessor or digital signal processor.

The amplifiers 230 may operate in two phases, and a controller (notshown) may control the timing of the amplifiers 230 in the two phases.The first phase may be defined when the amplifier 230 may be reset byclosing the reset switch, thereby discharging the capacitors. The secondphase may be defined when the voltage is integrated using the transferfunction. The timing for the CTIA reset and integration phases may besynchronized by the microprocessor in the signal processor 150 tochanges in the asymmetrical and compensation voltages applied to theanalytical region 130. The CTIA is reset during transition changes untilthe voltage levels have settled. The integration phase starts after thevoltage levels have settled. The CTIA amplifier prevents noiseinterference by synchronization of the CTIA reset and integration phasesto changes in the analytical voltage levels so that voltage changetransients are not integrated by the capacitors.

The integration time may be relatively short, e.g., on the order ofmilliseconds, as shown in FIG. 6B. In one exemplary embodiment, theintegration time may be about 10 milliseconds or less. This integrationtime may be significantly shorter than the detection time inconventional TOF-IMS and DMS spectrometers. Moreover, with the CTIAamplifier, the gain may be changed depending on various environments.For example, the CTIA amplifier gain may be increased by integratingover a longer period of time or by decreasing the value of integrationcapacitance. The gain may be lowered by integrating for a short time orincreasing the net capacitance. An exemplary timing diagram is shown inFIG. 6B.

The amplifiers 230 amplify the current and send the output in voltage tothe signal processor 150. The signal processor 150 may process theelectrical current at the various compensation voltages in thecompensation voltage range to identify a spectrum for the ionizedanalytes. The signal processor 150 may take the voltage from the one ormore amplifiers 230 and convert it into a digital value. The signalprocessor may also operate in modes that correspond to the two phases ofthe amplifiers 230 to conserve energy. For example, when the amplifier230 is in the integration phase, the signal processor may be in a“sleep” mode to conserve energy. In an exemplary embodiment, the signalprocessor 150 may only be in an “active” mode for the time it takes toreceive data from the amplifiers 300, run a predictive algorithm,identify the compounds of interest, and send output to the readoutdisplay 160. At all other times, the signal processor 150 may be in“sleep” mode. Using a CTIA amplifier allows the signal processor tooperate in multiple power saving modes.

The signal processor 150 may automatically vary the compensation voltageover a compensation voltage range for a given electric field to producea spectrum of ionized analytes in the sample gas identifying theintensity of the ionized analytes at a particular compensation voltage.The spectrum of ionized analytes also may identify the intensity of anydopants or other molecules in the carrier gas. Intensity may refer tothe amount of electrical current measured at a particular compensationvoltage, for example. The compensation voltage range may be a range ofvoltages from a positive voltage to a negative voltage, between twopositive voltages, or between two negative voltages. The spectrum ofionized analytes may be referred to as a mobility scan, an ionogram, oran ion spectra.

Chemical species within the carrier gas may be identified based uponcorrelation of the spectrum of the ionized analytes in the carrier gaswith previously determined spectra for known chemical species. Thespectrum of ionized analytes produces peaks based on an amount ofelectrical current detected at various compensations voltages. Thespectrum of ionized analytes may be compared against stored spectra ofknown compounds and/or molecules for the device 100 based on the appliedelectric field to identify whether a match exists between the samplespectrum and any spectra of known chemical species. A match with aspectrum of a known chemical species may indicate that the sample gasincludes the known chemical species.

In an exemplary embodiment, the signal processor 150 compares thespectrum for the ionized analytes with various spectra for knownchemical species and may determine whether a match exists. If a matchexists, the signal processor 150 may output data indicating that thesample gas contains one or more chemical species based on the match withthe known spectrum or spectra. The output data indicating a match may bevisible or audible on the readout display 160. If a match does notexist, the signal processor 150 may output data indicating that thesample gas does not match any known chemical species. Again, the outputdata indicating a non-match may be visible or audible on the readoutdisplay 160.

As recited above, temperature and moisture exert a substantial influenceon ion behavior in DMS spectrometers. Specifically, moisture or humidityaffect the peak locations of chemical species, and even though moisturecan be controlled within some macroscopic range, very small changes inthe humidity may cause the peaks to change location. To further assistwith identifying species of interest, a prediction model may be used topredict the effect of moisture on peak locations of ions of interest. Toaccommodate these changes in peak location, the device 100 was adaptedto accurately identify compounds and chemical species at variousmoisture levels. In an exemplary embodiment, an empirical model wasdeveloped using a known reactant ion peak (RIP) to accurately predictchemical species with the device 100 based on where that RIP appears. Apredictive methodology may be used in the device that may be sensitiveto changes in moisture or humidity levels, to identify peaks of interestin relationship to the RIP.

FIGS. 7A and 7B show the effect of moisture on the sample spectrum ofthe nerve agent GB. The nerve agent GB was measured at a variety ofmoisture levels to determine the effect of moisture on peak location.FIG. 7A shows a dry spectrum of GB, and FIG. 7B shows a wet spectrum ofGB. As can be seen, the sample spectrum shows a shift in peak locationsimply based on the moisture level in the system. In DMS systems, thisshift in peak location may lead to more accurate and reliable resultsbecause of the peak separation. However, the device 100 may beconfigured to predict the location of the peak of a chemical of interestdepending on the level of moisture. To design the device 100 capable ofaccurately identifying chemical species regardless of the amount ofmoisture that results in different peak locations for a given species,an engineering model was developed to gather empirical data for chemicalspecies at various moisture levels, a set of data was gathered, and amathematical trend was determined for each agent of interest.

FIG. 8A shows how the RIP moves as the moisture levels are changed fromdry conditions, to wet conditions, back to dry conditions. The datacollected for GB was then plotted in a graph, as shown in FIG. 5B, whichdisplays the mathematical trend developed for a GB peak based on themoisture level. The centerline of the graph shows the relationship ofthe reactant ion peak to a GB peak. The outside bounds represent astatistical confidence level, which allows the device 100 to predictwith confidence the existence of GB.

In an exemplary embodiment, this prediction methodology data, generatedfor all components whether chemical, biological, etc., may be stored inthe device 100. This data allows the device 100 to accurately predictthe existence of chemical species under the influence of moisture (whichrelates to the humidity in the air). The prediction methodology enablesthe device 100 to predict the peak location of chemical species when theRIP location is known. In other words, in an unknown environment, theknown RIP may be determined, and from that, using the mathematical trendprogrammed in the device 100, analytes may be detected based on thestored data.

FIG. 9 illustrates an exemplary embodiment of a spectrum of ionizedanalytes in a carrier gas. FIG. 9 illustrates a spectrum generated basedon GB ions included in the carrier gas with the ion intensity beingidentified on the vertical axis (i.e., y axis), and the compensationvoltage being identified on the horizontal axis (i.e., x axis) of thebottom plot for a specific dispersion voltage. FIG. 9 illustratesdetected GB ions forming a peak intensity at a compensation voltagearound −18 volts. Future detections of a peak at this compensationvoltage may indicate detection of GB in the sample gas.

FIG. 10 illustrates a flow diagram of an exemplary method 1000 fordetecting chemical species based on analytes in a carrier gas, accordingto an exemplary embodiment of the device 100. This exemplary method 1000is provided by way of example, as there are a variety of ways to carryout methods according to the present disclosure. The method 1000 shownin FIG. 10 can be executed or otherwise performed by one or acombination of various systems. The method 1000 is described below ascarried out by the device 100, as described above, and various elementsof the device 100 are referenced in explaining the example method ofFIG. 10. Each block shown in FIG. 10 represents one or more processes,methods, and/or subroutines carried out in the exemplary method.

In 1002, the device 100 receives sample gas. For example, a sample gasenters the inlet system 110 from an ambient environment. The inletsystem may comprise a membrane 206 to selectively separate analytes ofinterests and filter the sample gas.

In 1004, sample gas is ionized. For example, the sample gas may beionized over an ionization source, such as Ni63, to generate ions.

In 1006, ions are filtered in the analytical region 130. For example,the ions may be carried by a carrier gas through two filter electrodesthat apply an asymmetric, alternating electric field and a compensationfield to separate the ions. The signal generator may be used to generatethe electric field along with various compensation voltages over acompensation voltage range between the filter electrodes in theanalytical region for filtering ionized analytes within the carrier gas.

In 1008, the ions are detected. For example, the filtered ions may betransported in the carrier gas and collide with the collectorelectrodes. The collision generates an electrical current bytransferring the charge of the ionized analytes to the collectorelectrodes. Each collector electrode may be connected to a CTIAamplifier for converting the charge into voltage.

In 1010, the signal processor digitizes the information from the CTIAamplifier and compares the spectrum for the ionized analytes withvarious spectra for known chemical species and may determine whether amatch exists. For example, the signal processor may be programmed with apredictive methodology algorithm capable of identifying species atvarious moisture levels.

FIG. 11 illustrates a flow diagram of an algorithm process 1100 toidentify an ion species based using a known reactant ion peak, accordingto an exemplary embodiment of the device 100. This exemplary process1100 is provided by way of example, as there are a variety of ways tocarry out processes according to the present disclosure. The process1100 shown in FIG. 11 can be executed or otherwise performed by one or acombination of various systems. The method 1100 is described below ascarried out by the device 100, as described above, and various elementsof the device 100 are referenced in explaining the example method ofFIG. 11. Each block shown in FIG. 1I represents one or more processes,methods, and/or subroutines carried out in the exemplary method.

The process 1100 begins at step 1102 when spectral data is collected forchemical species at various moisture levels. In step 1104, a RIPlocation is determined for chemical species at each moisture level. Instep 1106, the reactant ion peak of a chemical species of interest isfound in the device 100 by using methods described above. In step 1108,the chemical species of interest is detected based on stored data. Instep 1110, the results (chemical identification) is sent to a readoutdisplay where they may be audibly or visibly displayed.

It will be apparent to those skilled in the art that variousmodifications and variations can be made in the method of manufacture ofthe present invention and in construction and use of this vapor detectorwithout departing from the scope or spirit of the invention. Otherembodiments of the invention will be apparent to those skilled in theart from consideration of the specification and practice of theinvention disclosed herein. It is intended that the specification beconsidered as exemplary only, with a true scope and spirit of theinvention being indicated by the following claims.

Accordingly, while the present invention has been described here indetail in relation to its exemplary embodiments, it is to be understoodthat this disclosure is only illustrative and exemplary of the presentinvention and is made to provide an enabling disclosure of theinvention. Accordingly, the foregoing disclosure is not intended to beconstrued or to limit the present invention or otherwise to exclude anyother such embodiments, adaptations, variations, modifications andequivalent arrangements.

1. A method for identifying chemical species in a sample, the method including the steps of: introducing a sample gas into a differential ion mobility device; ionizing at least a portion of the sample gas to generate at least one ion species; filtering the at least one ion species between a pair of filter electrodes; generating a detection signal using a capacitance trans impedance amplifier (CTIA) in response to the at least one ion species depositing a charge on a collector electrode, the CTIA sending the detection signal to a signal processor; detecting a spectral peak associated with the at least one ion species by processing the detection signal; and utilizing a prediction model to predict a moisture effect on the at least one ion species and referencing a data store to identify an unknown compound in the species.
 2. The method of claim 1, wherein the sample gas is introduced from an ambient environment.
 3. The method of claim 1, wherein filtering the at least one ion is performed by applying an asymmetric, alternating electric field adapted to influence the mobility behavior of the at least one ion species traveling between the pair of filter electrodes.
 4. The method of claim 3, wherein the substantially asymmetric, alternating electric field is controlled by a signal generator that selectively adjusts the field and causing the at least one ion species to be separated.
 5. The method of claim 1, wherein the CTIA comprises an input for receiving a current signal from the collector electrode and an output for outputting a voltage signal to a signal processor, and at least one feedback charge storage capacitor coupled between the input and output.
 6. The method of claim 5, wherein the CTIA comprises at least one reset switch coupled between the input and output and in parallel with the at least one feedback charge storage capacitor, the at least one feedback charge being discharged in response to the reset switch periodically being activated, thereby ending an integration period.
 7. The method of claim 1, wherein the CTIA operates in an integration phase and a reset phase, the integration phase adapted to integrate the CTIA over a period of time, and the reset phase adapted to discharge the at least one capacitors, the CTIA being operatively coupled to a controller for controlling the timing of the integration phase and reset phase.
 8. The method of claim 6, wherein the CTIA comprises at least one additional capacitor in parallel with at least one feedback charge storage capacitor to vary the gain of the CTIA.
 9. The method of claim 1 further comprising the step of conveying the detected spectral peak either audibly or visibly to a display.
 10. A device for identifying chemical species in a sample gas, the device comprising: an inlet adapted to receive a sample gas, the inlet being selectively separated from an ionization region that ionizes the sample gas to generate ions; a filter having at least a pair of oppositely disposed filter electrodes defining an analytical gap between which a substantially asymmetric field is generated, the substantially asymmetric field being controllable by a signal generator, wherein the filter separates the ions based on ion mobility characteristics; at least one collector electrode adapted to receive the ions, the collector being coupled to an capacitive trans impedance amplifier (CTIA); a prediction model adapted to predict a moisture effect on the ions; a signal processor adapted to receive an output voltage generated by the CTIA in order to detect a spectral peak associated with the ions; and a data store for identifying an unknown compound in the species.
 11. The device of claim 10, wherein the filter applies a compensation field as a DC voltage in addition to the asymmetric field, the filter comprising a range of the applied substantially asymmetric field and compensation field.
 12. The device of claim 11, wherein the substantially asymmetric field and the compensation field are controlled by a signal generator to change with substantially asymmetric field and the compensation field with time.
 13. The device of claim 10, wherein the CTIA comprises an input for receiving a current signal from the collector electrode and an output for outputting a voltage signal to a signal processor, and at least one feedback charge storage capacitor coupled between the input and output, the first feedback charge storage capacitor having a value.
 14. The device of claim 10, wherein the CTIA comprises at least one reset switch coupled between the input and output and in parallel with the first feedback charge storage capacitor, the reset switch periodically discharging the at least one feedback charge storage capacitor to start a new integration period.
 15. The device of claim 14, wherein a controller is adapted to synchronize the CTIA to reset at the time in which the asymmetric field and compensation fields are changed within the filter.
 16. The device of claim 15, wherein the CTIA remains in a reset state until the asymmetric field and compensation fields are changed within the filter so as to substantially reduce noise sent to the CTIA during the filter changes.
 17. The device of claim 14, wherein the controller is adapter to synchronize the CTIA to begin the integration phase after the asymmetric field and compensation fields are in a steady state condition.
 18. The device of claim 10 comprising a readout display configured to display, either visibly or audibly, the detected spectral peak.
 19. The device of claim 14, wherein the device sensitivity and selectivity can be dynamically adjusted in real-time by increasing or decreasing the integration phase of the CTIA or increasing or decreasing the integration capacitor(s) of the CTIA.
 20. The device of claim 14, wherein an array of CTIAs is used.
 21. The device of claim 10, wherein the inlet is heated. 